Scientists developed a way of using artificial intelligence to check for skin cancer with the AI tool, which was trained on data from 53,601 skin lesions from 25,105 patients, outperforming existing methods in a new study.
Scientists in the East of England have developed a way of using artificial intelligence to check for skin cancer , with the AI tool outperforming existing methods in a new study.
Researchers applied proportional weighting to these seven features to create the new C4C Risk Score which has an accuracy of 69%. In the study it significantly outperformed existing methods such as 7PCL and Williams score . "Our new AI model, which combines the C4C risk score together with skin lesion images, could lead to a reduction in the need for patient referrals for biopsies, shorter waiting times for skin cancer diagnosis and treatment, and improved outcomes for patients."
"The NHS is deluged with referrals for skin lesion analysis -- the vast majority are in fact innocent. This work is geared towards sifting out lesions that are potentially serious and identifying those patients whose skin is more prone to developing cancers so they can be seen quickly."
Skin Cancer Psoriasis Cosmetic Surgery Computer Modeling Artificial Intelligence Mathematical Modeling Statistics
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